Gender: Male 
Age: 55-60
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Married 
First language: English 
Religion: Nothing 
Education: High school or below
Mother's education: High school or below
Father's education: Undergraduate degree
Self-assessed socioeconomic status (1-10): 3
Home: Rent 
Employment: Self-employed part time
Occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations);Homemaker;Technicians and associate professionals (those who apply scientific or artistic concepts and operational methods, e.g. secretaries, fitness workers, lab technicians)
Mother's occupation: Homemaker
Father's occupation: Manager or business owner (those who plan, direct, coordinate and evaluate the overall activities of enterprises, governments and other organizations)
Hobbies: Listen to rock/indie music;Exercise;Do arts and crafts;Listen to jazz;Listen to classical music;Use social media;Other (Please specify) Reading, streaming, cooking, coding a game project
Devices used daily: Smartwatch;Smartphone;Other PC
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Claude;Google Gemini;Character.AI;Other DeepSeek
LLM use cases: Brainstorming;Writing (e.g., composing emails);Proofreading/Editing (e.g., grammar, spelling, structure improvements);Generic chatbot conversation;Solving math or logical problems;Generate art;Learning (e.g., explaining complex concepts in simple terms);Get information about current events;Answering questions about general knowledge;Summarizing long texts;Paraphrasing or finding synonyms 
Contexts of LLM use: Entertainment;Learning;Personal;Creative or artistic;Technical 
Prompt 1: Coding assistance
Prompt 2: Idea generation
Prompt 3: Resolving questions about health
Prompt 4: Resolving complex philisophical questions
Prompt 5: Summarization
Prompt 6: Looking up information and summarizing it
Prompt 7: Learning
Prompt 8: Image creation
Prompt 9: Image stylization